Analytics and the Internet of Things

The original conception of the Internet of Things (IoT) was of a network of physical objects or “things” embedded with electronics, software, sensors, and connectivity to enable objects to exchange data with a centralized operator and/or other connected devices.

Smart grids, smart homes and smart cities were all representations of what an IoT could be/do.

The IoT equivalent of the human brain is the cloud-based analysis of the data rising up from sensors to generate insights and decide on actions. Much of the benefit of the Internet of Things lies in our ability to leverage the (useful) data we collect with it. This is the “analytics of things,” and this area has, in many ways, received the least attention of all. This is unfortunate, because it is analytics that can add the most business, lifestyle, and health value to the IoT. It has been said that “data without meaning, without soul, will not move people to change their behaviors over the long term.”1 Value-added analytics are what many early adopters of activity trackers believe has been most missing and disappointing.

Sensor data have some unique attributes, so related analytics are unique as well. The data are typically continuous and fast-flowing, so there must be processes for continuous analysis of the data. Technologies such as “complex event processing” and “event stream processing” bring the data to the analysis capability, where they are processed in real time, and then results are sent back where they are needed. Because there is so much data, a major focus of the analytics of things is anomaly detection. Is something broken in our operational network? Does a bike ride appear to be in the middle of a corn field? Are you about to end the day without reaching 10,000 steps? Analytics can identify situations that require some form of human intervention.

Some other typical analytical applications for the IoT include the following:

  • Comparative usage—how your consumption of a resource (for example, calories) compares with others in similar situations
  • Understanding patterns and reasons for variation—developing statistical models that explain variation
  • Predictive asset maintenance—using sensor data to detect potential problems in machinery (or your body) before they actually occur
  • Optimization—using sensor data and analysis to optimize a process, as when a lumber mill optimizes the automated cutting of a log, or a poultry processor automates the preparation of a chicken, or when is the healthiest time to go to sleep or when in your sleep cycle to wake up
  • Prescription—employing sensor and other types of data to tell the user what to do, as when an activity tracker nudges you to get off the couch or sit up straight
  • Situational awareness—piecing together seemingly disconnected events and relating them to a larger repository of data to put together an explanation, as when a series of readings from activity trackers, glucose monitors, connected scales, and other devices tells you that you are in danger of contracting diabetes

The analytics of things is often a precursor to cognitive action—taking action based on the results of analyzed sensor data. Comparative usage statistics, for example, might motivate an energy consumer to cut back on usage, while smart thermostats can monitor and optimize the household environment. Predictive asset maintenance suggests the best time to service machinery, which is usually much more efficient than servicing at predetermined intervals. A municipal government could analyze traffic data sensors in roads and other sources to determine where to add lanes and how to optimize stoplight timing and other drivers of traffic flow.

Most Active Smart Home Investors

CB Insights recently ranked the most active investors into unique smart home technology companies since 2012, including venture capital and corporate venture investors.

They define the smart home category as companies producing consumer-facing products that replace or augment existing home products such as appliances. These products must connect to a smartphone or the internet, or integrate sensors and digital interfaces. Continue reading “Most Active Smart Home Investors”

Is Ambient Intelligence the Future of IoT?

An condensed repost from the World Economic Forum

What technology industry analyst firm Gartner is calling “the device mesh” is the logical evolution of the Internet of Things. All around us and always on, it will be both ubiquitous and subtle — ambient intelligence.

In that envisioned future we’ll do truly different things, instead of just doing things differently. Today’s processes and problems are only a small subset of the many, many scenarios possible when practically everything is instrumented, interconnected, and intelligent.

Continue reading “Is Ambient Intelligence the Future of IoT?”

Surprising Stats Regarding The Internet Of Things

CMO.com publishes a weekly column, “Mind Blowing Stats”  that collects disparate and sometimes arcane data points about a specific topic.  A recent edition of the column highlighted the great traction and movement forward that IoT is achieving though most people, and companies, don’t recognize how fast the technology is being embraced.  From the column:

Continue reading “Surprising Stats Regarding The Internet Of Things”